Six-month atrophy in MTL structures is associated with subsequent memory decline in elderly controls

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

The Value of Neuroimaging in Dementia Diagnosis

PURPOSE OF REVIEW

This article discusses neuroimaging in dementia diagnosis, with a focus on new applications of MRI and positron emission tomography (PET).

RECENT FINDINGS

Although the historical use of MRI in dementia diagnosis has been supportive to exclude structural etiologies, recent innovations allow for quantification of atrophy patterns that improve sensitivity for supporting the diagnosis of dementia causes. Neuronuclear approaches allow for localization of specific amyloid and tau neuropathology on PET and are available for clinical use, in addition to dopamine transporter scans in dementia with Lewy bodies and metabolic studies with fludeoxyglucose PET (FDG-PET).

SUMMARY

Using computerized software programs for MRI analysis and cross-sectional and longitudinal evaluations of hippocampal, ventricular, and lobar volumes improves sensitivity in support of the diagnosis of Alzheimer disease and frontotemporal dementia. MRI protocol requirements for such quantification are three-dimensional T1-weighted volumetric imaging protocols, which may need to be specifically requested. Fluid-attenuated inversion recovery (FLAIR) and 3.0T susceptibility-weighted imaging (SWI) sequences are useful for the detection of white matter hyperintensities as well as microhemorrhages in vascular dementia and cerebral amyloid angiopathy. PET studies for amyloid and/or tau pathology can add additional specificity to the diagnosis but currently remain largely inaccessible outside of research settings because of prohibitive cost constraints in most of the world. Dopamine transporter PET scans can help identify Lewy body dementia and are thus of potential clinical value.

Cognitive and hippocampal changes weeks and years after memory training

While immediate effects of memory-training are widely reported in young and older adults, less is known regarding training-dependent hippocampal plasticity across multiple intervention phases, and long-term maintenance of such. Here, 157 healthy young and older adults underwent a training-intervention including two 10 weeks periods of episodic-memory training, separated by two 2 weeks periods of no training. Both age groups showed improvements on a criterion task, which prevailed after 3 years. When compared to the reference condition of no training, relative increases in hippocampal volume were observed after the training across age groups, which were maintained after 10 weeks periods of no training. However, there was age-group dependent temporal variation with respect to timing of effects. Hippocampal volume of the training group did not differ from that of a passive control-group 3 years after the intervention. The young showed an immediate near-transfer effect on a word-association task. We show that training-gains on memory performance can prevail for at least 3 years. Memory training can induce increases in hippocampal volume immediately after the intervention and after months. Episodic-memory training can produce transfer effects to a non-trained memory task in young adults. However, maintained effects on hippocampal volume beyond 10 weeks are uncertain, and likely require continuous training.

Concordance of Alzheimer’s Disease Subtypes Produced from Different Representative Morphological Measures: A Comparative Study

Background: Gray matter (GM) density and cortical thickness (CT) obtained from structural magnetic resonance imaging are representative GM morphological measures that have been commonly used in Alzheimer’s disease (AD) subtype research. However, how the two measures affect the definition of AD subtypes remains unclear. Methods: A total of 180 AD patients from the ADNI database were used to identify AD subgroups. The subtypes were identified via a data-driven strategy based on the density features and CT features, respectively. Then, the similarity between the two features in AD subtype definition was analyzed. Results: Four distinct subtypes were discovered by both density and CT features: diffuse atrophy AD, minimal atrophy AD (MAD), left temporal dominant atrophy AD (LTAD), and occipital sparing AD. The matched subtypes exhibited relatively high similarity in atrophy patterns and neuropsychological and neuropathological characteristics. They differed only in MAD and LTAD regarding the carrying of apolipoprotein E ε2. Conclusions: The results verified that different representative morphological GM measurement methods could produce similar AD subtypes. Meanwhile, the influences of apolipoprotein E genotype, asymmetric disease progression, and their interactions should be considered and included in the AD subtype definition. This study provides a valuable reference for selecting features in future studies of AD subtypes.

Specific and general relationships between cortical thickness and cognition in older adults: a longitudinal study

Prior studies suggest that relationships between regional cortical thickness and domain-specific cognitive performance can be mediated by the relationship between global cortical thickness and domain-general cognition. Whether such findings extend to longitudinal cognitive change remains unclear. Here, we examined the relationships in healthy older adults between cognitive performance, longitudinal cognitive change over 3 years, and cortical thickness at baseline of the left and right inferior frontal gyrus (IFG) and left and right hemispheres. Both right IFG and right hemisphere thickness predicted baseline general cognition and domain-specific cognitive performance. Right IFG thickness was also predictive of longitudinal memory change. However, right IFG thickness was uncorrelated with cognitive performance and memory change after controlling for the mean thickness of other ipsilateral cortical regions. In addition, most identified associations between cortical thickness and specific cognitive domains were nonsignificant after controlling for the variance shared with other cognitive domains. Thus, relationships between right IFG thickness, cognitive performance, and memory change appear to be largely accounted for by more generic relationships between cortical thickness and cognition. This article is part of the Virtual Special Issue titled "COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING". The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

A robust brain signature region approach for episodic memory performance in older adults

The brain signature concept aims to characterize brain regions most strongly associated with an outcome of interest. Brain signatures derive their power from data-driven searches that select features based solely on performance metrics of prediction or classification. This approach has important potential to delineate biologically relevant brain substrates for prediction or classification of future trajectories. Recent work has used exploratory voxel-wise or atlas-based searches, with some using machine learning techniques to define salient features. These have shown undoubted usefulness, but two issues remain. The preponderance of recent work has been aimed at categorical rather than continuous outcomes, and it is rare for non-atlas reliant voxel-based signatures to be reported that would be useful for modelling and hypothesis testing. We describe a cross-validated signature region model for structural brain components associated with baseline and longitudinal episodic memory across cognitively heterogeneous populations including normal, mild impairment and dementia. We used three non-overlapping cohorts of older participants: from the UC Davis Aging and Diversity cohort (n = 255; mean age 75.3 ± 7.1 years; 128 cognitively normal, 97 mild cognitive impairment, 30 demented and seven unclassified); from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 (n = 379; mean age 75.1 ± 7.2; 82 cognitively normal, 176 mild cognitive impairment, 121 Alzheimer's dementia); and from ADNI2/GO (n = 680; mean age 72.5 ± 7.1; 220 cognitively normal, 381 mild cognitive impairment and 79 Alzheimer's dementia). We used voxel-wise regression analysis, correcting for multiple comparisons, to generate an array of regional masks corresponding to different association strength levels of cortical grey matter with baseline memory and brain atrophy with memory change. Cognitive measures were episodic memory using Spanish and English Neuropsychological Assessment Scales instruments for UC Davis and ADNI-Mem for ADNI 1 and ADNI2/GO. Performance metric was the adjusted R2 coefficient of determination of each model explaining outcomes in two cohorts other than where it was computed. We compared within-cohort performances of signature models against each other and against other recent signature models of episodic memory. Findings were: (i) two independently generated signature region of interest models performed similarly in a third separate cohort; (ii) a signature region of interest generated in one imaging cohort replicated its performance level when explaining cognitive outcomes in each of other, separate cohorts; and (iii) this approach better explained baseline and longitudinal memory than other recent theory-driven and data-driven models. This suggests our approach can generate signatures that may be easily and robustly applied for modelling and hypothesis testing in mixed cognition cohorts.

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score

18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). The AD pathology is progressive, and leads to structural and functional alterations that lie on a continuum. There is a need to quantify the altered metabolism patterns that exist on a continuum into a simple measure. This work proposes a 3D convolutional neural network with residual connections that generates a probability score useful for interpreting the FDG-PET images along the continuum of AD. This network is trained and tested on images of stable normal control and stable Dementia of the Alzheimer's type (sDAT) subjects, achieving an AUC of 0.976 via repeated fivefold cross-validation. An independent test set consisting of images in between the two extreme ends of the DAT spectrum is used to further test the generalization performance of the network. Classification performance of 0.811 AUC is achieved in the task of predicting conversion of mild cognitive impairment to DAT for conversion time of 0-3 years. The saliency and class activation maps, which highlight the regions of the brain that are most important to the classification task, implicate many known regions affected by DAT including the posterior cingulate cortex, precuneus, and hippocampus.

Interference Control in Working Memory Is Associated with Ventrolateral Prefrontal Cortex Volume

Goal-irrelevant information may interfere with ongoing task activities if not controlled properly. Evidence suggests that the ability to control interference is connected mainly to the prefrontal cortex (pFC). However, it remains unclear whether gray matter (GM) volume in prefrontal regions influences individual differences in interference control (IC) and if these relationships are affected by aging. Using cross-sectional and longitudinal estimates over a 4- to 5-year period, we examined the relationship between relative IC scores, obtained from a 2-back working memory task, GM volumes, and performance in different cognitive domains. By identifying individuals with either no or high levels of interference, we demonstrated that participants with superior IC had larger volume of the ventrolateral pFC, regardless of participant demographics. The same pattern was observed both at baseline and follow-up. Cross-sectional estimates further showed that interference increased as a function of age, but interference did not change between baseline and follow-up. Similarly, across-sample associations between IC and pFC volume were found in the cross-sectional data, along with no longitudinal change-change relationships. Moreover, relative IC scores could be linked to composite scores of fluid intelligence, indicating that control of interference may relate to performance in expected cognitive domains. These results provide new evidence that a relative IC score can be related to volume of specific and relevant regions within pFC and that this relationship is not modulated by age. This supports a view that the GM volume in these regions plays a role in resisting interference during a working memory task.

Longitudinal Evidence for Increased Functional Response in Frontal Cortex for Older Adults with Hippocampal Atrophy and Memory Decline

The functional organization of the frontal cortex is dynamic. Age-related increases in frontal functional responses have been shown during various cognitive tasks, but the cross-sectional nature of most past studies makes it unclear whether these increases reflect reorganization or stable individual differences. Here, we followed 130 older individuals' cognitive trajectories over 20-25 years with repeated neuropsychological assessments every 5th year, and identified individuals with stable or declining episodic memory. Both groups displayed significant gray matter atrophy over 2 successive magnetic resonance imaging sessions 4 years apart, but the decline group also had a smaller volume of the right hippocampus. Only individuals with declining memory demonstrated increased prefrontal functional responses during memory encoding and retrieval over the 4-year interval. Regions with increased functional recruitment were located outside, or on the borders of core task-related networks, indicating an expansion of these over time. These longitudinal findings offer novel insight into the mechanisms behind age-associated memory loss, and are consistent with a theoretical model in which hippocampus atrophy, past a critical threshold, induces episodic-memory decline and altered prefrontal functional organization.

Longitudinal Brain Atrophy Rates in Transient Ischemic Attack and Minor Ischemic Stroke Patients and Cognitive Profiles

Introduction: Patients with transient ischemic attack (TIA) and minor stroke demonstrate cognitive impairment, and a four-fold risk of late-life dementia. Aim: To study the extent to which the rates of brain volume loss in TIA patients differ from healthy controls and how they are correlated with cognitive impairment. Methods: TIA or minor stroke patients were tested with a neuropsychological battery and underwent T1 weighted volumetric magnetic resonance imaging scans at fixed intervals over a 3 years period. Linear mixed effects regression models were used to compare brain atrophy rates between groups, and to determine the relationship between atrophy rates and cognitive function in TIA and minor stroke patients. Results: Whole brain atrophy rates were calculated for the TIA and minor stroke patients; n = 38 between 24 h and 18 months, and n = 68 participants between 18 and 36 months, and were compared to healthy controls. TIA and minor stroke patients demonstrated a significantly higher whole brain atrophy rate than healthy controls over a 3 years interval (p = 0.043). Diabetes (p = 0.012) independently predicted higher atrophy rate across groups. There was a relationship between higher rates of brain atrophy and processing speed (composite P = 0.047 and digit symbol coding P = 0.02), but there was no relationship with brain atrophy rates and memory or executive composite scores or individual cognitive tests for language (Boston naming, memory recall, verbal fluency or Trails A or B score). Conclusion: TIA and minor stroke patients experience a significantly higher rate of whole brain atrophy. In this cohort of TIA and minor stroke patients changes in brain volume over time precede cognitive decline.

Reduced Gray Matter Volume of the Thalamus and Hippocampal Region in Elderly Healthy Adults with no Impact of APOE ɛ4: A Longitudinal Voxel-Based Morphometry Study

BACKGROUND

Many cross-sectional voxel-based morphometry (VBM) investigations have shown significant inverse correlations between chronological age and gray matter (GM) volume in several brain regions in healthy humans. However, few VBM studies have documented GM decrements in the healthy elderly with repeated MRI measurements obtained in the same subjects. Also, the extent to which the APOE ɛ4 allele influences longitudinal findings of GM reduction in the healthy elderly is unclear.

OBJECTIVE

Verify whether regional GM changes are associated with significant decrements in cognitive performance taking in account the presence of the APOE ɛ4 allele.

METHODS

Using structural MRI datasets acquired in 55 cognitively intact elderly subjects at two time-points separated by approximately three years, we searched for voxels showing significant GM reductions taking into account differences in APOE genotype.

RESULTS

We found global GM reductions as well as regional GM decrements in the right thalamus and left parahippocampal gyrus (p < 0.05, family-wise error corrected for multiple comparisons over the whole brain). These findings were not affected by APOE ɛ4.

CONCLUSIONS

Irrespective of APOE ɛ4, longitudinal VBM analyses show that the hippocampal region and thalamus are critical sites where GM shrinkage is greater than the degree of global volume reduction in healthy elderly subjects.

The 12-Word Philadelphia Verbal Learning Test Performances in Older Adults: Brain MRI and Cerebrospinal Fluid Correlates and Regression-Based Normative Data

Background/Aims

This study evaluated neuroimaging and biological correlates, psychometric properties, and regression-based normative data of the 12-word Philadelphia Verbal Learning Test (PVLT), a list-learning test.

Methods

Vanderbilt Memory and Aging Project participants free of clinical dementia and stroke (n = 230, aged 73 ± 7 years) completed a neuropsychological protocol and brain MRI. A subset (n = 111) underwent lumbar puncture for analysis of Alzheimer's disease (AD) and axonal integrity cerebrospinal fluid (CSF) biomarkers. Regression models related PVLT indices to MRI and CSF biomarkers adjusting for age, sex, race/ethnicity, education, APOE-ε4 carrier status, cognitive status, and intracranial volume (MRI models). Secondary analyses were restricted to participants with normal cognition (NC; n = 127), from which regression-based normative data were generated.

Results

Lower PVLT performances were associated with smaller medial temporal lobe volumes (p < 0.05) and higher CSF tau concentrations (p < 0.04). Among NC, PVLT indices were associated with white matter hyperintensities on MRI and an axonal injury biomarker (CSF neurofilament light; p < 0.03).

Conclusion

The PVLT appears sensitive to markers of neurodegeneration, including temporal regions affected by AD. Conversely, in cognitively normal older adults, PVLT performance seems to relate to white matter disease and axonal injury, perhaps reflecting non-AD pathways to cognitive change. Enhanced normative data enrich the clinical utility of this tool.

Educational Attainment Moderates the Association Between Hippocampal Volumes and Memory Performances in Healthy Older Adults

Objective: To examine whether educational attainment, as a proxy of cognitive reserve, moderated the association between hippocampal volumes and episodic verbal memory performances in healthy older adults.

Methods: Data from 76 community dwelling older adults were included in the present study. Measures of hippocampal volumes (total, left, and right) were obtained using FreeSurfer software. Immediate and delayed verbal recall scores were derived from performances on the California Verbal Learning Test-Second Edition and the Wechsler Memory Scale- Third Edition. Educational attainment was defined by years of education. Linear regression analyses were performed using immediate and delayed recall as dependent variables and hippocampal volumes, years of education, and their interaction terms as independent variables. All analyses were controlled for age, sex, depression, and health status.

Results: Total and left Hippocampal volumes had a positive main effect on delayed recall only. Additionally, the interaction between total, left, and right hippocampal volumes and education was a significant predictor for delayed recall performance but not for immediate recall performance. The positive association between hippocampal volumes and delayed recall was greatest in those with more years of education.

Conclusion: Larger hippocampal volumes were associated with better delayed verbal recall and the effect on delayed recall was greatest in those with more years of education. Having higher levels of education, or cognitive reserve, may enable individuals to capitalize on greater structural integrity in the hippocampus to support delayed recall in old age. However, longitudinal research is needed to investigate the directionality of these associations.

Multimodal cortical and hippocampal prediction of episodic-memory plasticity in young and older adults

Episodic memory can be trained in both early and late adulthood, but there is considerable variation in cognitive improvement across individuals. Which brain characteristics make some individuals benefit more than others? We used a multimodal approach to investigate whether volumetric magnetic resonance imaging (MRI) and resting-state functional MRI characteristics of the cortex and hippocampus, brain regions involved in episodic-memory function, were predictive of cognitive improvement after memory training. We hypothesized that these brain characteristics would differentially predict memory improvement in young and older adults, given the vulnerability of cortical regions as well as the hippocampus to healthy aging. Following structural and resting-state activity magnetic resonance scans, 50 young and 76 older participants completed 10 weeks of strategic episodic-memory training. Both age groups improved their memory performance, but the young adults more so than the older. Vertex-wise analyses of cortical volume showed no significant relation to memory benefit. When analyzing the two age groups separately, hippocampal volume was predictive of memory improvement in the group of older participants only. In this age group, the lower resting-state activity of the hippocampus was also predictive of memory improvement. Both volumetric and resting-state characteristics of the hippocampus explained unique variance of the improvement in the older participants suggesting that a multimodal imaging approach is valuable for the understanding of mechanisms underlying memory plasticity in aging.

Validity and Normative Data for the Biber Figure Learning Test: A Visual Supraspan Memory Measure

The Biber Figure Learning Test (BFLT), a visuospatial serial figure learning test, was evaluated for biological correlates and psychometric properties, and normative data were generated. Nondemented individuals (n = 332, 73 ± 7, 41% female) from the Vanderbilt Memory & Aging Project completed a comprehensive neuropsychological protocol. Adjusted regression models related BFLT indices to structural brain magnetic resonance imaging and cerebrospinal fluid (CSF) markers of brain health. Regression-based normative data were generated. Lower BFLT performances (Total Learning, Delayed Recall, Recognition) related to smaller medial temporal lobe volumes and higher CSF tau concentrations but not CSF amyloid. BFLT indices were most strongly correlated with other measures of verbal and nonverbal memory and visuospatial skills. The BFLT provides a comprehensive assessment of all aspects of visuospatial learning and memory and is sensitive to biomarkers of unhealthy brain aging. Enhanced normative data enriches the clinical utility of this visual serial figure learning test for use with older adults.

Brain volume change and cognitive trajectories in aging

OBJECTIVE

Examine how longitudinal cognitive trajectories relate to brain baseline measures and change in lobar volumes in a racially/ethnically and cognitively diverse sample of older adults.

METHOD

Participants were 460 older adults enrolled in a longitudinal aging study. Cognitive outcomes were measures of episodic memory, semantic memory, executive function, and spatial ability derived from the Spanish and English Neuropsychological Assessment Scales (SENAS). Latent variable multilevel modeling of the four cognitive outcomes as parallel longitudinal processes identified intercepts for each outcome and a second order global change factor explaining covariance among the highly correlated slopes. We examined how baseline brain volumes (lobar gray matter, hippocampus, and white matter hyperintensity) and change in brain volumes (lobar gray matter) were associated with cognitive intercepts and global cognitive change. Lobar volumes were dissociated into global and specific components using latent variable methods.

RESULTS

Cognitive change was most strongly associated with brain gray matter volume change, with strong independent effects of global gray matter change and specific temporal lobe gray matter change. Baseline white matter hyperintensity and hippocampal volumes had significant incremental effects on cognitive decline beyond gray matter change. Baseline lobar gray matter was related to cognitive decline, but did not contribute beyond gray matter change.

CONCLUSION

Cognitive decline was strongly influenced by gray matter volume change and, especially, temporal lobe change. The strong influence of temporal lobe gray matter change on cognitive decline may reflect involvement of temporal lobe structures that are critical for late life cognitive health but also are vulnerable to diseases of aging. (PsycINFO Database Record

Patterns of brain atrophy associated with episodic memory and semantic fluency decline in aging

The cerebral substratum of age-related cognitive decline was evaluated in an elderly-cohort followed for 12 years (n=306). Participants, free of dementia, received neuropsychological assessments every two years and an MRI exam at baseline and four years later. Cognitive decline was evaluated on two broadly used tests to detect dementia: the Free and Cued Selective Reminding Test (FCSRT), a verbal episodic memory task, and the Isaacs Set Test (IST), a semantic fluency task. Using voxel-based approach, the relationship between cognitive decline with 1/ baseline grey matter volumes and 2/ grey matter volume loss between the two scans was explored. Baseline volumes analysis revealed that FCSRT and IST declines were both associated with lower volumes of the medial temporal region. Volumes loss analysis confirmed that both declines are related to medial temporal lobe atrophy and revealed that FCSRT decline was specifically associated with atrophy of the posterior cingulate cortex whereas IST decline was specifically related to temporal pole atrophy. These results suggest that cognitive decline across aging is firstly related to structural modifications of the medial temporal lobe, followed by an atrophy in the posterior midline structures for episodic memory and an atrophy of the temporal pole for semantic fluency.

An Exploration Into Short-Interval Maintenance of Adult Hemispheric Cortical Thickness at an Individual Brain Level

Adult cerebral cortical structure is thought to be statically maintained over short intervals. This view is based on group average findings but has never been studied at the individual level. This issue was examined with an unconventional longitudinal magnetic resonance imaging design which measured hemispheric mean cortical thickness of an adult man repeatedly at week intervals over 6 months. These measures were compared with measurement error estimates to test the current prediction that thickness measures would be statically maintained within measurement error variation. The results did not support this prediction. Thickness underwent incremental and decremental fluctuations which ranged up to 0.12 mm and 5.83% over week and multiweek intervals and which differed from measurement error variation. These exploratory analyses suggest a working hypothesis that short-interval cortical structural maintenance in an individual can involve fluctuations in thickness. If confirmed, this hypothesis has potential implications for cortical maintenance mechanisms and precision medicine approaches.

Brain volumetric changes and cognitive ageing during the eighth decade of life

Later‐life changes in brain tissue volumes—decreases in the volume of healthy grey and white matter and increases in the volume of white matter hyperintensities (WMH)—are strong candidates to explain some of the variation in ageing‐related cognitive decline. We assessed fluid intelligence, memory, processing speed, and brain volumes (from structural MRI) at mean age 73 years, and at mean age 76 in a narrow‐age sample of older individuals (n = 657 with brain volumetric data at the initial wave, n = 465 at follow‐up). We used latent variable modeling to extract error‐free cognitive levels and slopes. Initial levels of cognitive ability were predictive of subsequent brain tissue volume changes. Initial brain volumes were not predictive of subsequent cognitive changes. Brain volume changes, especially increases in WMH, were associated with declines in each of the cognitive abilities. All statistically significant results were modest in size (absolute r‐values ranged from 0.114 to 0.334). These results build a comprehensive picture of macrostructural brain volume changes and declines in important cognitive faculties during the eighth decade of life. Hum Brain Mapp 36:4910–4925, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity

Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging.

Monitoring the early signs of cognitive decline in elderly by computer games: an MRI study

Background

It is anticipated that current and future preventive therapies will likely be more effective in the early stages of dementia, when everyday functioning is not affected. Accordingly the early identification of people at risk is particularly important. In most cases, when subjects visit an expert and are examined using neuropsychological tests, the disease has already been developed. Contrary to this cognitive games are played by healthy, well functioning elderly people, subjects who should be monitored for early signs. Further advantages of cognitive games are their accessibility and their cost-effectiveness.

Purpose

The aim of the investigation was to show that computer games can help to identify those who are at risk. In order to validate games analysis was completed which measured the correlations between results of the 'Find the Pairs' memory game and the volumes of the temporal brain regions previously found to be good predictors of later cognitive decline.

Participants and Methods

34 healthy elderly subjects were enrolled in the study. The volume of the cerebral structures was measured by MRI. Cortical reconstruction and volumetric segmentation were performed by Freesurfer.

Results

There was a correlation between the number of attempts and the time required to complete the memory game and the volume of the entorhinal cortex, the temporal pole, and the hippocampus. There was also a correlation between the results of the Paired Associates Learning (PAL) test and the memory game.

Conclusions

The results gathered support the initial hypothesis that healthy elderly subjects achieving lower scores in the memory game have increased level of atrophy in the temporal brain structures and showed a decreased performance in the PAL test. Based on these results it can be concluded that memory games may be useful in early screening for cognitive decline.

Effect of leukocyte telomere length on total and regional brain volumes in a large population-based cohort

IMPORTANCE

Telomere length has been associated with dementia and psychological stress, but its relationship with human brain size is unknown.

OBJECTIVE

To determine if peripheral blood telomere length is associated with brain volume.

DESIGN, SETTING, AND PARTICIPANTS

Peripheral blood leukocyte telomere length and brain volumes were measured for 1960 individuals in the Dallas Heart Study, a population-based, probability sample of Dallas County, Texas, residents, with a median (25th-75th percentile) age of 50 (42-58) years. Global and 48 regional brain volumes were assessed from the automated analysis of magnetic resonance imaging.

MAIN OUTCOMES AND MEASURES

Telomere length and global and regional brain volumes.

RESULTS

Leukocyte telomere length was associated with total cerebral volume (β [SE], 0.06 [0.01], P <.001) including white and cortical gray matter volume (β [SE], 0.04 [0.01], P = .002; β [SE], 0.07 [0.02], P <.001, respectively), independent of age, sex, ethnicity, and total intracranial volume. While age was associated with the size of most subsegmental regions of the cerebral cortex, telomere length was associated with certain subsegmental regions. Compared with age, telomere length (TL) explained a sizeable proportion of the variance in volume of the hippocampus, amygdala, and inferior temporal region (hippocampus: βTL [SE], 0.08 [0.02], R2, 0.91% vs βage [SE], -0.16 [0.02], R2, 3.80%; amygdala: βTL [SE], 0.08 [0.02], R2, 0.78% vs βage [SE],-0.19 [0.02], R2,4.63%; inferior temporal: βTL [SE], 0.07 [0.02], R2, 0.92% vs βage [SE], -0.14 [0.02], R2, 3.98%) (P <.001 for all). The association of telomere length and the size of the inferior and superior parietal, hippocampus, and fusiform regions was stronger in individuals older than 50 years than younger individuals (inferior parietal: β>50 [SE], 0.13 [0.03], P <.001 vs β≤50 [SE], 0.02 [0.02], P = .51, P for interaction = .001; superior parietal: β>50 [SE], 0.11 [0.03], P <.001 vs β≤50 [SE], 0.01 [0.02], P = .71, P for interaction = .004; hippocampus: β>50 [SE], 0.10 [0.03], P = .004 vs β≤50 [SE], 0.05 [0.02], P = .07, P for interaction = .04; fusiform: β>50 [SE], 0.09 [0.03], P = .002, β≤50 [SE], 0.03 [0.02], P = .31, P for interaction = .03). The volume of the hippocampus, amygdala, superior and inferior temporal, precuneus, lateral orbitofrontal, posterior cingulate, thalamus and ventral diencephalon were independently associated with telomere length after adjustment for all covariates (age, gender, ethnicity, total intracranial volume, body mass index, blood pressure, diabetes, smoking status, and APOE genotype).

CONCLUSIONS AND RELEVANCE

To our knowledge, this is the first population-based study to date to evaluate telomere length as an independent predictor of global and regional brain size. Future studies are needed to determine how telomere length and anatomic structural changes are related to cognitive function, dementia, and psychological disease.

Mapping ventricular expansion onto cortical gray matter in older adults

Dynamic changes in the brain's lateral ventricles on magnetic resonance imaging are powerful biomarkers of disease progression in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Ventricular measures can represent accumulation of diffuse brain atrophy with very high effect sizes. Despite having no direct role in cognition, ventricular expansion co-occurs with volumetric loss in gray and white matter structures. To better understand relationships between ventricular and cortical changes over time, we related ventricular expansion to atrophy in cognitively relevant cortical gray matter surfaces, which are more challenging to segment. In ADNI participants, percent change in ventricular volumes at 1-year (N = 677) and 2-year (N = 536) intervals was significantly associated with baseline cortical thickness and volume in the full sample controlling for age, sex, and diagnosis, and in MCI separately. Ventricular expansion in MCI was associated with thinner gray matter in frontal, temporal, and parietal regions affected by AD. Ventricular expansion reflects cortical atrophy in early AD, offering a useful biomarker for clinical trials of interventions to slow AD progression.

Reliability of brain volume measurements: a test-retest dataset

Evaluation of neurodegenerative disease progression may be assisted by quantification of the volume of structures in the human brain using magnetic resonance imaging (MRI). Automated segmentation software has improved the feasibility of this approach, but often the reliability of measurements is uncertain. We have established a unique dataset to assess the repeatability of brain segmentation and analysis methods. We acquired 120 T1-weighted volumes from 3 subjects (40 volumes/subject) in 20 sessions spanning 31 days, using the protocol recommended by the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject was scanned twice within each session, with repositioning between the two scans, allowing determination of test-retest reliability both within a single session (intra-session) and from day to day (inter-session). To demonstrate the application of the dataset, all 3D volumes were processed using FreeSurfer v5.1. The coefficient of variation of volumetric measurements was between 1.6% (caudate) and 6.1% (thalamus). Inter-session variability exceeded intra-session variability for lateral ventricle volume (P<0.0001), indicating that ventricle volume in the subjects varied between days.

What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimer's disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.

Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on univariate and multivariate models

RATIONALE AND OBJECTIVES

Differentiating mild cognitive impairment (MCI) and Alzheimer Disease (AD) from healthy aging remains challenging. This study aimed to explore the cerebral structural alterations of subjects with MCI or AD as compared to healthy elderly based on the individual and collective effects of cerebral morphologic indices using univariate and multivariate analyses.

MATERIALS AND METHODS

T1-weighted images (T1WIs) were retrieved from Alzheimer Disease Neuroimaging Initiative database for 116 subjects who were categorized into groups of healthy aging, MCI, and AD. Analysis of covariance (ANCOVA) and multivariate analysis of covariance (MANCOVA) were performed to explore the intergroup morphologic alterations indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume with age and sex controlled as covariates, in 34 parcellated gyri regions of interest (ROIs) for both cerebral hemispheres based on the T1WI. Statistical parameters were mapped on the anatomic images to facilitate visual inspection.

RESULTS

Global rather than region-specific structural alterations were revealed in groups of MCI and AD relative to healthy elderly using MANCOVA. ANCOVA revealed that the cortical thickness decreased more prominently in entorhinal, temporal, and cingulate cortices and was positively correlated with patients' cognitive performance in AD group but not in MCI. The temporal lobe features marked atrophy of white matter during the disease dynamics. Significant intercorrelations were observed among the morphologic indices with univariate analysis for given ROIs.

CONCLUSIONS

Significant global structural alterations were identified in MCI and AD based on MANCOVA model with improved sensitivity. The intercorrelation among the morphologic indices may dampen the use of individual morphological parameter in featuring cerebral structural alterations. Decrease in cortical thickness is not reflective of the cognitive performance at the early stage of AD.

A focus on structural brain imaging in the Alzheimer's disease neuroimaging initiative

In recent years, numerous laboratories and consortia have used neuroimaging to evaluate the risk for and progression of Alzheimer's disease (AD). The Alzheimer's Disease Neuroimaging Initiative is a longitudinal, multicenter study that is evaluating a range of biomarkers for use in diagnosis of AD, prediction of patient outcomes, and clinical trials. These biomarkers include brain metrics derived from magnetic resonance imaging (MRI) and positron emission tomography scans as well as metrics derived from blood and cerebrospinal fluid. We focus on Alzheimer's Disease Neuroimaging Initiative studies published between 2011 and March 2013 for which structural MRI was a major outcome measure. Our main goal was to review key articles offering insights into progression of AD and the relationships of structural MRI measures to cognition and to other biomarkers in AD. In Supplement 1, we also discuss genetic and environmental risk factors for AD and exciting new analysis tools for the efficient evaluation of large-scale structural MRI data sets such as the Alzheimer's Disease Neuroimaging Initiative data.

What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimer's disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.

Maturation of Cortico-Subcortical Structural Networks-Segregation and Overlap of Medial Temporal and Fronto-Striatal Systems in Development

The brain consists of partly segregated neural circuits within which structural convergence and functional integration occurs during development. The relationship of structural cortical and subcortical maturation is largely unknown. We aimed to study volumetric development of the hippocampus and basal ganglia (caudate, putamen, pallidum, accumbens) in relation to volume changes throughout the cortex. Longitudinal MRI data were obtained across a mean interval of 2.6 years in 85 participants with an age range of 8-19 years at study start. Left and right subcortical changes were related to cortical change vertex-wise in the ipsilateral hemisphere with general linear models with age, sex, interval between scans, and mean cortical volume change as covariates. Hippocampal-cortical change relationships centered on parts of the Papez circuit, including entorhinal, parahippocampal, and isthmus cingulate areas, and lateral temporal, insular, and orbitofrontal cortices in the left hemisphere. Basal ganglia-cortical change relationships were observed in mostly nonoverlapping and more anterior cortical areas, all including the anterior cingulate. Other patterns were unique to specific basal ganglia structures, including pre-, post-, and paracentral patterns relating to putamen change. In conclusion, patterns of cortico-subcortical development as assessed by morphometric analyses in part map out segregated neural circuits at the macrostructural level.

Risk factors for the progression of mild cognitive impairment to dementia

The increasing prevalence of cognitive impairment among the older adult population warrants attention to the identification of practices that may minimize the progression of early forms of cognitive impairment, including the transitional stage of mild cognitive impairment (MCI), to permanent stages of dementia. This article identifies both markers of disease progress and risk factors linked to the progression of MCI to dementia. Potentially modifiable risk factors may offer researchers a point of intervention to modify the effect of the risk factor and to minimize the future burden of dementia.

Understanding cognitive deficits in Alzheimer's disease based on neuroimaging findings

Brain amyloid can be measured using positron emission tomography (PET). There are mixed reports regarding whether amyloid measures are correlated with measures of cognition (in particular memory), depending on the cohorts and cognitive domains assessed. In Alzheimer's disease (AD) patients and those at heightened risk for AD, cognitive performance may be related to the level and extent of classical AD pathology (amyloid plaques and neurofibrillary angles), but it is also influenced by neurodegeneration, neurocognitive reserve, and vascular health. We discuss what recent neuroimaging research has discovered about cognitive deficits in AD and offer suggestions for future research.

Gray-matter macrostructure in cognitively healthy older persons: associations with age and cognition

A deeper understanding of brain macrostructure and its associations with cognition in persons who are considered cognitively healthy is critical to the early detection of persons at risk of developing dementia. Few studies have examined the associations of all three gray-matter macrostructural brain indices (volume, thickness, surface area) with age and cognition, in the same persons who are over the age of 65 and do not have cognitive impairment. We performed automated morphometric reconstruction of total gray matter, cortical gray matter, subcortical gray matter and 84 individual regions in 186 persons (60 % over the age of 80) without cognitive impairment. Morphometric measures were scaled and expressed as difference per decade of age and an adjusted score was created to identify those regions in which there was greater atrophy per decade of age compared to cortical or subcortical brain averages. The results showed that there is substantial total volume loss and cortical thinning in cognitively healthy older persons. Thinning was more widespread than volume loss, but volume loss, particularly in temporoparietal and hippocampal regions, was more strongly associated with cognition.

The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

Brain changes in older adults at very low risk for Alzheimer's disease

Alzheimer's disease (AD) has a slow onset, so it is challenging to distinguish brain changes in healthy elderly persons from incipient AD. One-year brain changes with a distinct frontotemporal pattern have been shown in older adults. However, it is not clear to what extent these changes may have been affected by undetected, early AD. To address this, we estimated 1-year atrophy by magnetic resonance imaging (MRI) in 132 healthy elderly persons who had remained free of diagnosed mild cognitive impairment or AD for at least 3 years. We found significant volumetric reductions throughout the brain. The sample was further divided into low-risk groups based on clinical, biomarker, genetic, or cognitive criteria. Although sample sizes varied, significant reductions were observed in all groups, with rates and topographical distribution of atrophy comparable to that of the full sample. Volume reductions were especially pronounced in the default mode network, closely matching the previously described frontotemporal pattern of changes in healthy aging. Atrophy in the hippocampus predicted change in memory, with no additional default mode network contributions. In conclusion, reductions in regional brain volumes can be detected over the course of 1 year even in older adults who are unlikely to be in a presymptomatic stage of AD.

Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI)

We sought to develop and evaluate a composite memory score from the neuropsychological battery used in the Alzheimer's Disease (AD) Neuroimaging Initiative (ADNI). We used modern psychometric approaches to analyze longitudinal Rey Auditory Verbal Learning Test (RAVLT, 2 versions), AD Assessment Schedule - Cognition (ADAS-Cog, 3 versions), Mini-Mental State Examination (MMSE), and Logical Memory data to develop ADNI-Mem, a composite memory score. We compared RAVLT and ADAS-Cog versions, and compared ADNI-Mem to RAVLT recall sum scores, four ADAS-Cog-derived scores, the MMSE, and the Clinical Dementia Rating Sum of Boxes. We evaluated rates of decline in normal cognition, mild cognitive impairment (MCI), and AD, ability to predict conversion from MCI to AD, strength of association with selected imaging parameters, and ability to differentiate rates of decline between participants with and without AD cerebrospinal fluid (CSF) signatures. The second version of the RAVLT was harder than the first. The ADAS-Cog versions were of similar difficulty. ADNI-Mem was slightly better at detecting change than total RAVLT recall scores. It was as good as or better than all of the other scores at predicting conversion from MCI to AD. It was associated with all our selected imaging parameters for people with MCI and AD. Participants with MCI with an AD CSF signature had somewhat more rapid decline than did those without. This paper illustrates appropriate methods for addressing the different versions of word lists, and demonstrates the additional power to be gleaned with a psychometrically sound composite memory score.

Differential brain shrinkage over 6 months shows limited association with cognitive practice

The brain shrinks with age, but the timing of this process and the extent of its malleability are unclear. We measured changes in regional brain volumes in younger (age 20-31) and older (age 65-80) adults twice over a 6 month period, and examined the association between changes in volume, history of hypertension, and cognitive training. Between two MRI scans, 49 participants underwent intensive practice in three cognitive domains for 100 consecutive days, whereas 23 control group members performed no laboratory cognitive tasks. Regional volumes of seven brain structures were measured manually and adjusted for intracranial volume. We observed significant mean shrinkage in the lateral prefrontal cortex, the hippocampus, the caudate nucleus, and the cerebellum, but no reliable mean change of the prefrontal white matter, orbital-frontal cortex, and the primary visual cortex. Individual differences in change were reliable in all regions. History of hypertension was associated with greater cerebellar shrinkage. The cerebellum was the only region in which significantly reduced shrinkage was apparent in the experimental group after completion of cognitive training. Thus, in healthy adults, differential brain shrinkage can be observed in a narrow time window, vascular risk may aggravate it, and intensive cognitive activity may have a limited effect on it.

Brain development and aging: overlapping and unique patterns of change

Early-life development is characterized by dramatic changes, impacting lifespan function more than changes in any other period. Developmental origins of neurocognitive late-life functions are acknowledged, but detailed longitudinal magnetic resonance imaging studies of brain maturation and direct comparisons with aging are lacking. To these aims, a novel method was used to measure longitudinal volume changes in development (n=85, 8-22 years) and aging (n=142, 60-91 years). Developmental reductions exceeded 1% annually in much of the cortex, more than double to that seen in aging, with a posterior-to-anterior gradient. Cortical reductions were greater than the subcortical during development, while the opposite held in aging. The pattern of lateral cortical changes was similar across development and aging, but the pronounced medial temporal reduction in aging was not precast in development. Converging patterns of change in adolescents and elderly, particularly in the medial prefrontal areas, suggest that late developed cortices are especially vulnerable to atrophy in aging. A key question in future research will be to disentangle the neurobiological underpinnings for the differences and the similarities between brain changes in development and aging.

Accelerating cortical thinning: unique to dementia or universal in aging?

Does accelerated cortical atrophy in aging, especially in areas vulnerable to early Alzheimer's disease (AD), unequivocally signify neurodegenerative disease or can it be part of normal aging? We addressed this in 3 ways. First, age trajectories of cortical thickness were delineated cross-sectionally (n = 1100) and longitudinally (n = 207). Second, effects of undetected AD on the age trajectories were simulated by mixing the sample with a sample of patients with very mild to moderate AD. Third, atrophy in AD-vulnerable regions was examined in older adults with very low probability of incipient AD based on 2-year neuropsychological stability, CSF Aβ(1-42) levels, and apolipoprotein ε4 negativity. Steady decline was seen in most regions, but accelerated cortical thinning in entorhinal cortex was observed across groups. Very low-risk older adults had longitudinal entorhinal atrophy rates similar to other healthy older adults, and this atrophy was predictive of memory change. While steady decline in cortical thickness is the norm in aging, acceleration in AD-prone regions does not uniquely signify neurodegenerative illness but can be part of healthy aging. The relationship between the entorhinal changes and changes in memory performance suggests that non-AD mechanisms in AD-prone areas may still be causative for cognitive reductions.

Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer's disease

Mild cognitive impairment (MCI) and Alzheimer's disease (AD) are associated with a progressive loss of cognitive abilities. In the present report, we assessed the relationship of memory and executive function with brain structure in a sample of 810 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, including 188 AD, 396 MCI, and 226 healthy older adults (HC). Composite scores of memory (ADNI-Mem) and executive function (ADNI-Exec) were generated by applying modern psychometric theory to item-level data from ADNI's neuropsychological battery. We performed voxel-based morphometry (VBM) and surface-based association (SurfStat) analyses to evaluate relationships of ADNI-Mem and ADNI-Exec with grey matter (GM) density and cortical thickness across the whole brain in the combined sample and within diagnostic groups. We observed strong associations between ADNI-Mem and medial and lateral temporal lobe atrophy. Lower ADNI-Exec scores were associated with advanced GM and cortical atrophy across broadly distributed regions, most impressively in the bilateral parietal and temporal lobes. We also evaluated ADNI-Exec adjusted for ADNI-Mem, and found associations with GM density and cortical thickness primarily in the bilateral parietal, temporal, and frontal lobes. Within-group analyses suggest these associations are strongest in patients with MCI and AD. The present study provides insight into the spatially unbiased associations between brain atrophy and memory and executive function, and underscores the importance of structural brain changes in early cognitive decline.

Enrichment and stratification for predementia Alzheimer disease clinical trials

The tau and amyloid pathobiological processes underlying Alzheimer disease (AD) progresses slowly over periods of decades before clinical manifestation as mild cognitive impairment (MCI), then more rapidly to dementia, and eventually to end-stage organ failure. The failure of clinical trials of candidate disease modifying therapies to slow disease progression in patients already diagnosed with early AD has led to increased interest in exploring the possibility of early intervention and prevention trials, targeting MCI and cognitively healthy (HC) populations. Here, we stratify MCI individuals based on cerebrospinal fluid (CSF) biomarkers and structural atrophy risk factors for the disease. We also stratify HC individuals into risk groups on the basis of CSF biomarkers for the two hallmark AD pathologies. Results show that the broad category of MCI can be decomposed into subsets of individuals with significantly different average regional atrophy rates. By thus selectively identifying individuals, combinations of these biomarkers and risk factors could enable significant reductions in sample size requirements for clinical trials of investigational AD-modifying therapies, and provide stratification mechanisms to more finely assess response to therapy. Power is sufficiently high that detecting efficacy in MCI cohorts should not be a limiting factor in AD therapeutics research. In contrast, we show that sample size estimates for clinical trials aimed at the preclinical stage of the disorder (HCs with evidence of AD pathology) are prohibitively large. Longer natural history studies are needed to inform design of trials aimed at the presymptomatic stage.

Parallel but not equivalent: challenges and solutions for repeated assessment of cognition over time

OBJECTIVE

Analyses of individual differences in change may be unintentionally biased when versions of a neuropsychological test used at different follow-ups are not of equivalent difficulty. This study's objective was to compare mean, linear, and equipercentile equating methods and demonstrate their utility in longitudinal research.

STUDY DESIGN AND SETTING

The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE, N = 1,401) study is a longitudinal randomized trial of cognitive training. The Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 819) is an observational cohort study. Nonequivalent alternate versions of the Auditory Verbal Learning Test (AVLT) were administered in both studies.

RESULTS

Using visual displays, raw and mean-equated AVLT scores in both studies showed obvious nonlinear trajectories in reference groups that should show minimal change and poor equivalence over time (ps ≤ .001), and raw scores demonstrated poor fits in models of within-person change (root mean square errors of approximation, RMSEAs > 0.12). Linear and equipercentile equating produced more similar means in reference groups (ps ≥ .09) and performed better in growth models (RMSEAs < 0.05).

CONCLUSION

Equipercentile equating is the preferred equating method because it accommodates tests more difficult than a reference test at different percentiles of performance and performs well in models of within-person trajectory. The method has broad applications in both clinical and research settings to enhance the ability to use nonequivalent test forms.

Models of the aging brain structure and individual decline

The aging brain's structural development constitutes a spatiotemporal process that is accessible by MR-based computational morphometry. Here we introduce basic concepts and analytical approaches to quantify age-related differences and changes in neuroanatomical images of the human brain. The presented models first address the estimation of age trajectories, then we consider inter-individual variations of structural decline, using a repeated measures design. We concentrate our overview on preprocessed neuroanatomical images of the human brain to facilitate practical applications to diverse voxel- and surface-based structural markers. Together these methods afford analysis of aging brain structure in relation to behavioral, health, or cognitive parameters.

Structural imaging in early pre-states of dementia

In this review focus is on structural imaging in the Alzheimer's disease (AD) pre-states, particularly cognitively normal (CN) persons at future dementia risk. Findings in mild cognitive impairment (MCI) are described here only for comparison with CN. Cited literature evidence and commentary address issues of structural imaging alterations in CN that precede MCI and AD, regional patterns of such alterations, and the time relationship between structural imaging alterations and the appearance of symptoms of AD, issues relevant to the conduct of future AD prevention trials. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

CETP polymorphisms associate with brain structure, atrophy rate, and Alzheimer's disease risk in an APOE-dependent manner

Two alleles in cholesteryl ester transfer protein (CETP) gene polymorphisms have been disputably linked to enhanced cognition and decreased risk of Alzheimer's disease (AD): the V and A alleles of I405V and C-629A. This study investigates whether these polymorphisms affect brain structure in 188 elderly controls and 318 AD or mild cognitive impairment (MCI) subjects from the Alzheimer's Disease Neuroimaging Initiative cohort. Nominally signficant associations were dependent on APOE ε4 carrier status. In APOE ε4 carriers, the V and A alleles, both of which decrease CETP and increase HDL, associated with greater baseline cortical thickness and less 12-month atrophy in the medial temporal lobe. Conversely, in APOE ε4 non-carriers, the I allele, which increases CETP and decreases HDL, associated with greater baseline thickness, less atrophy and lower risk of dementia. These results suggest CETP may contribute to the genetic variability of brain structure and dementia susceptibility in an APOE-dependent manner.

A two-study comparison of clinical and MRI markers of transition from mild cognitive impairment to Alzheimer's disease

A published predictor model in a single-site cohort study (questionable dementia, QD) that contained episodic verbal memory (SRT total recall), informant report of function (FAQ), and MRI measures was tested using logistic regression and ROC analyses with comparable measures in a second multisite cohort study (Alzheimer's Disease Neuroimaging Initiative, ADNI). There were 126 patients in QD and 282 patients in ADNI with MCI followed for 3 years. Within each sample, the differences in AUCs between the statistical models were very similar. Adding hippocampal and entorhinal cortex volumes to the model containing AVLT/SRT, FAQ, age and MMSE increased the area under the curve (AUC) in ADNI but not QD, with sensitivity increasing by 2% in ADNI and 2% in QD for a fixed specificity of 80%. Conversely, adding episodic verbal memory (SRT/AVLT) and FAQ to the model containing age, Mini Mental State Exam (MMSE), hippocampal and entorhinal cortex volumes increased the AUC in ADNI and QD, with sensitivity increasing by 17% in ADNI and 10% in QD for 80% specificity. The predictor models showed similar differences from each other in both studies, supporting independent validation. MRI hippocampal and entorhinal cortex volumes showed limited added predictive utility to memory and function measures.